title: Antiviral regimen complexity index as an independent predictor of sustained virologic response in patients with chronic hepatitis C.
abstract: BACKGROUND
  Hepatitis C virus (HCV) infection affects more than 170 million people worldwide, and one-third of them have human immunodeficiency virus (HIV) coinfection. Multiple studies have been conducted in order to identify the factors that may explain different responses to treatment among patients. However, the reasons why HIV-HCV coinfected patients have lower responses to treatment are not clear. In addition, no studies have evaluated the influence of the complexity of the therapeutic regimen for hepatitis C infection on clinical outcomes.
  
  
  OBJECTIVE
  To (a) investigate the influence of the antiviral regimen complexity in the sustained viral response (SVR) in patients with chronic hepatitis and (b) adapt a method of quantifying complexity of an antiretroviral regimen for patients infected with HCV.
  
  
  METHODS
  A single center, retrospective study was conducted in HCV and HIV-HCV coinfected patients. We selected patients treated with interferon alfa-2a plus ribavirin between January 2005 and December 2010. Patients with severe psychiatric disorders, those included in a clinical trial, and those known to be nonadherent to treatment were excluded. The dependent variable was the sustained virologic response and the independent variables were sex, age, race, stage fibrosis (F) ≥2, presence or absence of cirrhosis, low hepatitis C baseline viral load (defined as ≤800,000 IU), viral genotype, rapid virological response (RVR), serum gamma-glutamyltransferase (GGT) levels, ratio of alanine aminotransferase to aspartate aminotransferase (ALT/AST), serum cholesterol level, presence or absence of diabetes mellitus, and antiviral regimen complexity index. The latter variable included drugs for HCV and HIV infection, but no medication for other comorbidities. To evaluate the complexity of antiviral treatment we performed an adaptation of the system developed by Martin et al. (2007) in HIV patients. The factors determining the complexity of treatment were the number of medications, dosing schedules, administration methods, special instructions, and required preparations associated with antiviral regimens.  Sample size was estimated by the Freeman equation. To determine the independent variables associated with SVR, we performed an univariate logistic regression and subsequently a multivariate analysis with those variables that demonstrated a statistically significant difference in the univariate analysis.
  
  
  RESULTS
  A total of 156 patients was included (76% men, mean age 44 years) of whom 45% were HIV-HCV coinfected. 75% were genotypes 1 or 4. The univariate analysis variables-genotypes 2 and 3 (OR=3.10; CI [1.38-6.95]; P=0.006); HIV-HCV coinfection (OR=0.36; CI [0.19-0.69]); presence of cirrhosis (OR=0.27; CI [0.10-0.73]; P=0,01); F≥2 (OR=0.44; CI [0.23-0.84]; P=0.01); low baseline viral load (OR= 2.05; CI [1.01-4.17]; P=0.048); RVR (OR=17,60; CI [6.84-45.30]; P less than 0.001); complexity index (OR=0.71; CI [0.58-0.87]; P=0.001), showed statistically significant relationships with SVR. Complexity index (OR=0.67; CI [0.52-0.87]; P=0.002) and RVR (OR=20.04; CI [7.33-54.85]; P less than 0.001) were independent predictors of SVR in multivariate analysis. The reliability of the multivariate analysis was checked with the Hosmer and Lemeshow test (P=0.079).
  
  
  CONCLUSIONS
  The medication regimen complexity may be a crucial factor to achieve therapeutic success when treating patients for hepatitis C. The adaptation of this index in patients with HCV provides an objective value of the antiviral regimen complexity and could help us to identify patients in clinical practice who require multidisciplinary attention. Simplification of the antiretroviral regimen might result in a greater response to treatment for hepatitis C.
authors.affiliation: Valme University Hospital, Avenida de Bellavista S/N, 41014, Seville, Spain. jimenezgalanrocio@gmail.com
authors.forename: Rocío Jiménez
authors.initials: RJ
authors.lastname: Galán
authors.forename: Elena Calvo
authors.initials: EC
authors.lastname: Cidoncha
authors.forename: Mónica Ferrit
authors.initials: MF
authors.lastname: Martin
authors.forename: Concepción Carrascosa
authors.initials: CC
authors.lastname: Rodriguez
authors.forename: Carmen V
authors.initials: CV
authors.lastname: Almeida
authors.forename: Ramón Morillo
authors.initials: RM
authors.lastname: Verdugo
mesh_terms: D000328:Adult; D019380:Anti-HIV Agents / Q000627:therapeutic use; D000998:Antiviral Agents / Q000008:administration & dosage / Q000009:adverse effects / Q000627:therapeutic use*; D060085:Coinfection; D015897:Comorbidity; D004334:Drug Administration Schedule; D004359:Drug Therapy, Combination; D005260:Female; D005838:Genotype; D015658:HIV Infections / Q000175:diagnosis / Q000188:drug therapy / Q000453:epidemiology; D016174:Hepacivirus / Q000187:drug effects* / Q000235:genetics / Q000254:growth & development; D019698:Hepatitis C, Chronic / Q000175:diagnosis / Q000188:drug therapy* / Q000453:epidemiology; D006801:Humans; D016898:Interferon-alpha / Q000008:administration & dosage / Q000009:adverse effects / Q000627:therapeutic use*; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D016017:Odds Ratio; D011092:Polyethylene Glycols / Q000008:administration & dosage / Q000009:adverse effects / Q000627:therapeutic use*; D019338:Polypharmacy; D011994:Recombinant Proteins / Q000008:administration & dosage / Q000009:adverse effects / Q000627:therapeutic use; D012189:Retrospective Studies; D012254:Ribavirin / Q000008:administration & dosage / Q000009:adverse effects / Q000627:therapeutic use*; D012307:Risk Factors; D013030:Spain / Q000453:epidemiology; D013997:Time Factors; D016896:Treatment Outcome; D019562:Viral Load
chemical_list: D019380:Anti-HIV Agents; D000998:Antiviral Agents; D016898:Interferon-alpha; D011994:Recombinant Proteins; D011092:Polyethylene Glycols; D012254:Ribavirin; C100416:peginterferon alfa-2a